Oximetry is the measurement of the oxygen status of blood. Early detection of low blood oxygen is critical in the medical field, for example in critical care and surgical applications, because an insufficient supply of oxygen can result in brain damage and death in a matter of minutes. Pulse oximetry is a widely accepted noninvasive procedure for measuring the oxygen saturation level of arterial blood, an indicator of oxygen supply. A pulse oximeter typically provides a numerical readout of the patient""s oxygen saturation, a numerical readout of pulse rate, and an audible indicator or xe2x80x9cbeepxe2x80x9d that occurs at each pulse.
A pulse oximetry system consists of a sensor attached to a patient, a monitor, and a cable connecting the sensor and monitor. Conventionally, a pulse oximetry sensor has both red and infrared (IR) light-emitting diode (LED) emitters and a photodiode detector. The sensor is typically attached to an adult patient""s finger or an infant patient""s foot. For a finger, the sensor is configured so that the emitters project light through the fingernail and into the blood vessels and capillaries underneath. The photodiode is positioned at the fingertip opposite the fingernail so as to detect the LED emitted light as it emerges from the finger tissues.
The pulse oximetry monitor (pulse oximeter) determines oxygen saturation by computing the differential absorption by arterial blood of the two wavelengths emitted by the sensor. The pulse oximeter alternately activates the sensor LED emitters and reads the resulting current generated by the photodiode detector. This current is proportional to the intensity of the detected light. The pulse oximeter calculates a ratio of detected red and infrared intensities, and an arterial oxygen saturation value is empirically determined based on the ratio obtained. The pulse oximeter contains circuitry for controlling the sensor, processing the sensor signals and displaying the patient""s oxygen saturation and pulse rate. In addition, a pulse oximeter may display the patient""s plethysmograph waveform, which is a visualization of blood volume change in the illuminated tissue caused by arterial blood flow over time. A pulse oximeter is described in U.S. Pat. No. 5,632,272 assigned to the assignee of the present invention.
FIG. 1 illustrates the standard plethysmograph waveform 100, which can be derived from a pulse oximeter. The waveform 100 is a display of blood volume, shown along the y-axis 110, over time, shown along the x-axis 120. The shape of the plethysmograph waveform 100 is a function of heart stroke volume, pressure gradient, arterial elasticity and peripheral resistance. The ideal waveform 100 displays a broad peripheral flow curve, with a short, steep inflow phase 130 followed by a 3 to 4 times longer outflow phase 140. The inflow phase 130 is the result of tissue distention by the rapid blood volume inflow during ventricular systole. During the outflow phase 140, blood flow continues into the vascular bed during diastole. The end diastolic baseline 150 indicates the minimum basal tissue perfusion. During the outflow phase 140 is a dicrotic notch 160, the nature of which is disputed. Classically, the dicrotic notch 160 is attributed to closure of the aortic valve at the end of ventricular systole. However, it may also be the result of reflection from the periphery of an initial, fast propagating, pressure pulse that occurs upon the opening of the aortic valve and that precedes the arterial flow wave. A double dicrotic notch can sometimes be observed, although its explanation is obscure, possibly the result of reflections reaching the sensor at different times.
FIG. 2 is a graph 200 illustrating a compartmental model of the absorption of light at a tissue site illuminated by a pulse oximetry sensor. The graph 200 has a y-axis 210 representing the total amount of light absorbed by the tissue site, with time shown along an x-axis 220. The total absorption is represented by layers, including the static absorption layers due to tissue 230, venous blood 240 and a baseline of arterial blood 250. Also shown is a variable absorption layer due to the pulse-added volume of arterial blood 260. The profile 270 of the pulse-added arterial blood 260 is seen as the plethysmograph waveform 100 depicted in FIG. 1.
FIG. 3 illustrates the photo-plethysmograph intensity signal 300 detected by a pulse oximeter sensor. A pulse oximeter does not directly detect absorption and, hence, does not directly measure the standard plethysmograph waveform 100 (FIG. 1). However, the standard plethysmograph can be derived by observing that the detected intensity signal 300 is merely an out of phase version of the absorption profile 270. That is, the peak detected intensity 372 occurs at minimum absorption 272 (FIG. 2), and the minimum detected intensity 374 occurs at maximum absorption 274 (FIG. 2). Further, a rapid rise in absorption 276 (FIG. 2) during the inflow phase of the plethysmograph is reflected in a rapid decline 376 in intensity, and the gradual decline 278 (FIG. 2) in absorption during the outflow phase of the plethysmograph is reflected in a gradual increase 378 in detected intensity.
In addition to blood oxygen saturation, a desired pulse oximetry parameter is the rate at which the heart is beating, i.e. the pulse rate. At first glance, it seems that it is an easy task to determine pulse rate from the red and infrared plethysmograph waveforms described above. However, this task is complicated, even under ideal conditions, by the variety of physiological plethysmographic waveforms. Further, plethysmographic waveforms are often corrupted by noise, including motion artifact, as described in U.S. Pat. No. 2,632,272 cited above. Plethysmograph pulse recognition, especially in the presence of motion artifact and other noise sources, is a useful component for determining pulse rate and also for providing a visual or audible indication of pulse occurrence.
In one aspect of the pulse recognition processor according to the present invention, information regarding pulses within an input plethysmograph waveform is provided at a processor output. The processor has a candidate pulse portion that determines a plurality of potential pulses within the input waveform. A physiological model portion of the processor then determines the physiologically acceptable ones of these potential pulses. The processor may further provide statistics regarding the acceptable pulses. One statistic is pulse density, which is the ratio of the period of acceptable pulses to the duration of an input waveform segment.
The candidate pulse portion has a series of components that remove from consideration as potential pulses those waveform portions that do not correspond to an idealized triangular waveform. This processing removes irrelevant waveform features such as the characteristic dicrotic notch and those caused by noise or motion artifact. The candidate pulse portion provides an output having indices that identify potential pulses relative to the peaks and valleys of this triangular waveform.
The physiological model portion of the processor has a series of components that discard potential pulses that do not compare to a physiologically acceptable pulse. The first component of the model portion extracts features of the potential pulses, including pulse starting point, pulse period, and pulse signal strength. These features are compared against various checks, including checks for pulses that have a period below a predetermined threshold, that are asymmetric, that have a descending trend that is generally slower that a subsequent ascending trend, that do not sufficiently comply with an empirical relationship between pulse rate and pulse signal strength, and that have a signal strength that differs from a short-term average signal strength by greater than a predetermined amount.
In another aspect of the present invention, a pulse recognition method includes the steps of identifying a plurality of potential pulses in an input waveform and comparing the potential pulses to a physiological pulse model to derive at least one physiologically acceptable pulse. A further step of generating statistics for acceptable pulses may also be included. The generating step includes the steps of determining a total period of acceptable pulses and calculating a ratio of this total period to a duration of an input waveform segment to derive a pulse density value. The comparing step includes the steps of extracting pulse features from potential pulses and checking the extracted features against pulse criteria.
Yet another aspect of the current invention is a pulse recognition processor having a candidate pulse means for identifying potential pulses in an input waveform and providing a triangular waveform output. The processor also has a plethysmograph model means for determining physiologically acceptable pulses in the triangular waveform output and providing as a pulse output the indices of acceptable pulses. The pulse recognition processor may further have a pulse statistics means for determining cumulative pulse characteristics from said pulse output.